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- W3013101664 abstract "We discuss estimation problems where a polynomial is observed under Ornstein Uhlenbeck noise over a long time interval. We prove local asymptotic normality (LAN) and specify asymptotically efficient estimators. We apply this to the following problem: feeding noise into the classical (deterministic) Hodgkin Huxley model of neuroscience, we are interested in asymptotically efficient estimation of the parameters of the noise process." @default.
- W3013101664 created "2020-04-03" @default.
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- W3013101664 date "2020-03-30" @default.
- W3013101664 modified "2023-10-01" @default.
- W3013101664 title "Polynomials under Ornstein-Uhlenbeck noise and an application to inference in stochastic Hodgkin-Huxley systems" @default.
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